Clustering and Cache Coordination

An application cluster is a set of middle tier server machines or VMs servicing requests for a single application, or set of applications. Multiple servers are used to increase the scalability of the application and/or to provide fault tolerance and high availability. Typically the same application will be deployed to all of the servers in the cluster and application requests will be load balanced across the set of servers. The application cluster will access a single database, or a database cluster. An application cluster may allow new servers to be added to increase scalability, and for servers to be removed such as for updates and servicing.

EclipseLink can function in any clustered environment. The main issue in a clustered environment is utilizing a shared persistence unit (L2) cache. If you are using a shared cache (enabled by default in EclipseLink), then each server will maintain its own cache, and each caches data can get out of sync with the other servers and the database.

EclipseLink provides cache coordination in a clustered environment to ensure the servers caches are is sync.

There are also many other solutions to caching in a clustered environment, including:

Use optimistic locking to ensure write consistency (writes on stale data will fail, and will automatically invalidate the cache).

Use a distributed cache (such as Oracle TopLink Grid's integration of EclipseLink with Oracle Coherence).

Use database events to invalidate changed data in the cache (such as EclipseLink's support for Oracle DCN/QCN).

Cache coordination enables a set of persistence units deployed to different servers in the cluster (or on the same server) to synchronize their changes. Cache coordination works by each persistence unit on each server in the cluster being able to broadcast notification of transactional object changes to the other persistence units in the cluster. EclipseLink supports cache coordination over RMI and JMS. The cache coordination framework is also extensible so other options could be developed.

Cache coordination works by broadcasting changes for each transaction to the other servers in the cluster. Each other server will receive the change notification, and either invalidate the changed objects in their cache, or update the cached objects state with the changes. Cache coordination occurs after the database commit, so only committed changes are broadcast.

Cache coordination greatly reduces to chance of an application getting stale data, but does not eliminate the possibility. Optimistic locking should still be used to ensure data integrity. Even in a single server application stale data is still possible within a persistence context unless pessimistic locking is used. Optimistic (or pessimistic) locking is always required to ensure data integrity in any multi-user system.